imdecode jpeg2000 segfault or deadlock in multithreading

Expected behaviour

In the main thread, it works well as written in the example bellow:

import multiprocessing.pool
import cv2
import numpy as np
import tqdm
 
img = np.random.randint(0, 65335, (1024, 1024), dtype=np.uint16)
_, img_data = cv2.imencode(".jp2", img)
n = 100
 
def read(i):
    image = cv2.imdecode(buffer, cv2.IMREAD_ANYDEPTH | cv2.IMREAD_GRAYSCALE)
 
list(tqdm.tqdm(map(read, range(n)), total=n, desc="main thread main process"))
with multiprocessing.pool.Pool() as pool:
   list(tqdm.tqdm(pool.imap_unordered(read, range(n)), total=n, desc="main thread child process"))

Actual behaviour

But in a thread, it is all broken!

import multiprocessing.pool
import cv2
import numpy as np
import tqdm
 
img = np.random.randint(0, 65335, (1024, 1024), dtype=np.uint16)
_, img_data = cv2.imencode(".jp2", img)
n = 100
 
def read(i):
    image = cv2.imdecode(buffer, cv2.IMREAD_ANYDEPTH | cv2.IMREAD_GRAYSCALE)
 
with multiprocessing.pool.ThreadPool() as pool:
   list(tqdm.tqdm(pool.imap_unordered(read, range(n)), total=n, desc="child thread main process"))

When the code does not freeze by itself, an interrupt with ctrl+c leads allways to a segfault. Unlike the threadless example.

Steps to reproduce

• Tested on Debian, Ubuntu and Mint
• Version 4.9.0 of opencv-contrib-python-headless
• Tested on python 3.9, 3.10, 3.11 and 3.12
• architecture x86

Commencez avec le reproducteur Python ThreadPool fourni et comparez-le au cas multiprocessing Pool dans les environnements Python et basés sur Debian indiqués. Vérifiez la configuration du tampon et observez si le décodage JPEG2000 s’achève sans problème avec des threads concurrents ; cela est considéré comme terminé lorsqu’il n’y a ni deadlock ni segfault et que le décodage réussit lors des appels répétés.